milvus/internal/core/src/common/FieldData.h
Spade A 7cb15ef141
feat: impl StructArray -- optimize vector array serialization (#44035)
issue: https://github.com/milvus-io/milvus/issues/42148

Optimized from
Go VectorArray → VectorArray Proto → Binary → C++ VectorArray Proto →
C++ VectorArray local impl → Memory
to
Go VectorArray → Arrow ListArray  → Memory

---------

Signed-off-by: SpadeA <tangchenjie1210@gmail.com>
2025-09-03 16:39:53 +08:00

205 lines
6.2 KiB
C++

// Licensed to the LF AI & Data foundation under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#pragma once
#include <string>
#include <memory>
#include <utility>
#include <oneapi/tbb/concurrent_queue.h>
#include "common/FieldDataInterface.h"
#include "common/Channel.h"
#include "common/ArrowDataWrapper.h"
namespace milvus {
template <typename Type>
class FieldData : public FieldDataImpl<Type, true> {
public:
static_assert(IsScalar<Type> || std::is_same_v<Type, PkType>);
explicit FieldData(DataType data_type,
bool nullable,
int64_t buffered_num_rows = 0)
: FieldDataImpl<Type, true>::FieldDataImpl(
1, data_type, nullable, buffered_num_rows) {
}
static_assert(IsScalar<Type> || std::is_same_v<Type, PkType>);
explicit FieldData(DataType data_type,
bool nullable,
FixedVector<Type>&& inner_data)
: FieldDataImpl<Type, true>::FieldDataImpl(
1, data_type, nullable, std::move(inner_data)) {
}
};
template <>
class FieldData<std::string> : public FieldDataStringImpl {
public:
static_assert(IsScalar<std::string> || std::is_same_v<std::string, PkType>);
explicit FieldData(DataType data_type,
bool nullable,
int64_t buffered_num_rows = 0)
: FieldDataStringImpl(data_type, nullable, buffered_num_rows) {
}
};
template <>
class FieldData<Json> : public FieldDataJsonImpl {
public:
static_assert(IsScalar<std::string> || std::is_same_v<std::string, PkType>);
explicit FieldData(DataType data_type,
bool nullable,
int64_t buffered_num_rows = 0)
: FieldDataJsonImpl(data_type, nullable, buffered_num_rows) {
}
};
template <>
class FieldData<Array> : public FieldDataArrayImpl {
public:
static_assert(IsScalar<Array> || std::is_same_v<std::string, PkType>);
explicit FieldData(DataType data_type,
bool nullable,
int64_t buffered_num_rows = 0)
: FieldDataArrayImpl(data_type, nullable, buffered_num_rows) {
}
};
template <>
class FieldData<VectorArray> : public FieldDataVectorArrayImpl {
public:
explicit FieldData(int64_t dim,
DataType element_type,
int64_t buffered_num_rows = 0)
: FieldDataVectorArrayImpl(DataType::VECTOR_ARRAY, buffered_num_rows),
dim_(dim),
element_type_(element_type) {
AssertInfo(element_type != DataType::NONE,
"element_type must be specified for VECTOR_ARRAY");
}
int64_t
get_dim() const override {
return dim_;
}
DataType
get_element_type() const {
return element_type_;
}
void
set_element_type(DataType element_type) {
element_type_ = element_type;
}
const VectorArray*
value_at(ssize_t offset) const {
AssertInfo(offset < get_num_rows(),
"field data subscript out of range");
AssertInfo(offset < length(),
"subscript position don't has valid value");
return &data_[offset];
}
private:
int64_t dim_;
DataType element_type_;
};
template <>
class FieldData<FloatVector> : public FieldDataImpl<float, false> {
public:
explicit FieldData(int64_t dim,
DataType data_type,
int64_t buffered_num_rows = 0)
: FieldDataImpl<float, false>::FieldDataImpl(
dim, data_type, false, buffered_num_rows) {
}
};
template <>
class FieldData<BinaryVector> : public FieldDataImpl<uint8_t, false> {
public:
explicit FieldData(int64_t dim,
DataType data_type,
int64_t buffered_num_rows = 0)
: FieldDataImpl(dim / 8, data_type, false, buffered_num_rows),
binary_dim_(dim) {
Assert(dim % 8 == 0);
}
int64_t
get_dim() const override {
return binary_dim_;
}
private:
int64_t binary_dim_;
};
template <>
class FieldData<Float16Vector> : public FieldDataImpl<float16, false> {
public:
explicit FieldData(int64_t dim,
DataType data_type,
int64_t buffered_num_rows = 0)
: FieldDataImpl<float16, false>::FieldDataImpl(
dim, data_type, false, buffered_num_rows) {
}
};
template <>
class FieldData<BFloat16Vector> : public FieldDataImpl<bfloat16, false> {
public:
explicit FieldData(int64_t dim,
DataType data_type,
int64_t buffered_num_rows = 0)
: FieldDataImpl<bfloat16, false>::FieldDataImpl(
dim, data_type, false, buffered_num_rows) {
}
};
template <>
class FieldData<SparseFloatVector> : public FieldDataSparseVectorImpl {
public:
explicit FieldData(DataType data_type, int64_t buffered_num_rows = 0)
: FieldDataSparseVectorImpl(data_type, buffered_num_rows) {
}
};
template <>
class FieldData<Int8Vector> : public FieldDataImpl<int8, false> {
public:
explicit FieldData(int64_t dim,
DataType data_type,
int64_t buffered_num_rows = 0)
: FieldDataImpl<int8, false>::FieldDataImpl(
dim, data_type, false, buffered_num_rows) {
}
};
using FieldDataPtr = std::shared_ptr<FieldDataBase>;
using FieldDataChannel = Channel<FieldDataPtr>;
using FieldDataChannelPtr = std::shared_ptr<FieldDataChannel>;
FieldDataPtr
InitScalarFieldData(const DataType& type, bool nullable, int64_t cap_rows);
} // namespace milvus